Hi Tessa,
It is my understanding you want to know how to find optimal set of parameters using Latin Hypercube Design in combination with Gaussian process regression in MATLAB.
Using Latin Hypercube Design you could produce simulation data as shown below:
data = lhsdesign(n,p); % here p represents variables i.e. p = 2 in your case, and for each variables (B and C),
% the n values are randomly distributed with one from each interval (0,1/n), (1/n,2/n), ..., (1-1/n,1)
Then, fit Gaussian process regression model on the data using fitrgp.
- Refer to lhsdesign and lhsnorm documentations to produce Latin Hypercube samples.
- Refer to LHS DOE app which generates Latin Hypercube distribution.
- Refer to RegressionGP class and fitrgp documentations to fit Gaussian process regression model.
